



'''simple docstring'''





from __future__ import annotations

import math
from collections.abc import Callable




def 							lowerCamelCase	(					_snake_case	:    Optional[Any]  ,_snake_case	:    Optional[Any]  ,_snake_case	:    Union[str, Any]  ,_snake_case	:    Optional[Any] = 100  ,):





    '''simple docstring'''


    lowercase__									=    x_start
    lowercase__									=    fnc(_A							)
    lowercase__									=    0.0

    for _ in range(_A							):
        # Approximates curve as a sequence of linear lines and sums their length
        lowercase__									=    (x_end - x_start) / steps + xa
        lowercase__									=    fnc(_A							)
        length += math.hypot(xa - xa  ,fxa - fxa							)

        # Increment step
        lowercase__									=    xa
        lowercase__									=    fxa

    return length


if __name__ == "__main__":




 def 							lowerCamelCase	(					_snake_case	:    Dict							):





     '''simple docstring'''


     return math.sin(10 * x							)

 print("f(x) = sin(10 * x)")
 print("The length of the curve from x = -10 to x = 10 is:")
 SCREAMING_SNAKE_CASE__          =  10
 while i <= 10_0000:
  print(f'''With {i} steps: {line_length(f, -10, 10, i)}''')
  i *= 10









'''simple docstring'''






# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
     from PIL import Image

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       """Salesforce/blip-image-captioning-base"""
    lowercase__					=       (
        """This is a tool that generates a description of an image. It takes an input named `image` which should be the """
        """image to caption, and returns a text that contains the description in English."""
    )
    lowercase__					=       """image_captioner"""
    lowercase__					=       AutoModelForVisionaSeq

    lowercase__					=       ["""image"""]
    lowercase__					=       ["""text"""]







    def __init__( self					:    Tuple		,     *__snake_case					:    int		,     **__snake_case					:    List[Any]      ):
      requires_backends(self		,     ['vision']      )
      super().__init__(*__snake_case		,     **__snake_case      )







    def      lowercase_			( self					:    Optional[int]		,     __snake_case					:    "Image"      ):
      return self.pre_processor(images=__snake_case		,     return_tensors='pt'      )







    def      lowercase_			( self					:    Optional[Any]		,     __snake_case					:    str      ):
      return self.model.generate(**__snake_case      )







    def      lowercase_			( self					:    Optional[Any]		,     __snake_case					:    Tuple      ):
      return self.pre_processor.batch_decode(__snake_case		,     skip_special_tokens=__snake_case      )[0].strip()